Measurements of High Energy Cosmic Rays and Cloud presence: A method to estimate Cloud Coverage in Space and Ground-Based Infrared Images

Authors: Anzalone, A., Bruno, A. and Isgrò, F.

Journal: Nuclear and Particle Physics Proceedings

Volume: 306-308

Pages: 116-123

ISSN: 2405-6014

DOI: 10.1016/j.nuclphysbps.2019.07.017

Abstract:

Several projects and already-operative observatories aimed at detecting High Energy Cosmic Rays (HECR) are/will be equipped with instruments to monitor the atmosphere. Since cloud presence can affect the night-time indirect measurements of the HECRs and Cherenkov radiation, it is crucial to know the meteorological conditions during the observation period of the HECR detectors. Several meteorological satellites already provide useful information, however to obtain accurate reconstructions of the detected events it is more suitable using devices that operate synchronously with the main detector. To this purpose, infrared cameras that acquire images of the whole field of view are thought to support the atmosphere monitoring during observations from both space and ground. Meaningful parameters, like cloud coverage and cloud top/bottom height, can be retrieved from the analysis of those data. Multi-spectral information are typically analyzed and combined to obtain cloud masks for each image, where a cloudy/cloud-free probability flag is associated with each pixel. These algorithms normally use several spectral bands that are not always available in non-meteorological sensors. A different approach is presented in this paper. It only relies on the gray level values of the image pixel, and it can be applied on thermal infrared as well as visible images acquired from both space and ground. To test the method on real cloudy scenes, images from polar satellite and all-sky data archives are considered, and the results are compared to the corresponding cloudiness masks provided by the same data repositories.

Source: Scopus

Measurements of High Energy Cosmic Rays and Cloud presence: A method to estimate Cloud Coverage in Space and Ground-Based Infrared Images

Authors: Anzalone, A., Bruno, A. and Isgro, F.

Journal: NUCLEAR AND PARTICLE PHYSICS PROCEEDINGS

Volume: 306

Pages: 116-123

eISSN: 1873-3832

ISSN: 2405-6014

DOI: 10.1016/j.nuclphysbps.2019.07.017

Source: Web of Science (Lite)

Measurements of High Energy Cosmic Rays and Cloud presence: A method to estimate Cloud Coverage in Space and Ground-Based Infrared Images

Authors: Anzalone, A., Bruno, A. and Isgrò, F.

Journal: Nuclear and Particle Physics Proceedings

Volume: 306-308

Issue: CRIS 2018 "Entering the Era of Multi-Messenger Astronomy"

Pages: 116-123

Publisher: Elsevier

ISSN: 2405-6014

Abstract:

Several projects and already-operative observatories aimed at detecting High Energy Cosmic Rays (HECR) are/will be equipped with instruments to monitor the atmosphere. Since cloud presence can affect the night-time indirect measurements of the HECRs and Cherenkov radiation, it is crucial to know the meteorological conditions during the observation period of the HECR detectors. Several meteorological satellites already provide useful information, however to obtain accurate reconstructions of the detected events it is more suitable using devices that operate synchronously with the main detector. To this purpose, infrared cameras that acquire images of the whole field of view are thought to support the atmosphere monitoring during observations from both space and ground. Meaningful parameters, like cloud coverage and cloud top/bottom height, can be retrieved from the analysis of those data. Multi-spectral information are typically analyzed and combined to obtain cloud masks for each image, where a cloudy/cloud-free probability flag is associated with each pixel. These algorithms normally use several spectral bands that are not always available in non-meteorological sensors. A different approach is presented in this paper. It only relies on the gray level values of the image pixel, and it can be applied on thermal infrared as well as visible images acquired from both space and ground. To test the method on real cloudy scenes, images from polar satellite and all-sky data archives are considered, and the results are compared to the corresponding cloudiness masks provided by the same data repositories.

Source: Manual